2-D DOA and mutual coupling coefficient estimation for arbitrary array structures with single and multiple snapshots

Elbir, Ahmet M.; Tuncer, T. Engin

doi:10.1016/j.dsp.2016.03.011

Cited by 26 publications

(12 citation statements)

References 38 publications

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“…This effect is reduced for larger apertures resulting from the radar movement, because the targets are then in the effective near-field of the full aperture. Nevertheless, it is favorable and a common simplification to reduce the number of parameters in C by exploiting the array structure [8], [22], [31]. For this purpose, it is assumed that at first the signal couples between the antennas, described by the matrix Z.…”

Section: G Problem Relaxation For Uniform Linear Arraysmentioning

confidence: 99%

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Antenna Array Calibration Using a Sparse Scene

Geiß

Sippel

Hehn

et al. 2021

IEEE Open J. Antennas Propag.

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In radar systems, antenna arrays acquire direction-dependent information to localize targets or create images of the environment. However, because of unknown complex amplitudes per channel and mutual coupling, a calibration is necessary for good performance. Common calibration approaches measure to targets under known angles in a multipath-free far-field environment, which often can only be provided by anechoic chambers. Therefore, this process is not suitable for low-cost and frequent calibration. To overcome these limitations, this paper proposes a novel calibration approach using an unknown but sparse target scene. Multiple measurements at known relative positions of the radar are combined to a synthetic aperture. Then, the full mutual coupling matrix is estimated simultaneously with the unknown target scene. The method requires neither target position information, far-field conditions, nor an anechoic chamber because multipath propagation can be suppressed easily for targets located in the near-field. The proposed calibration approach is validated by measurements of a commercial 77 GHz radar. The performance is evaluated by comparing the achieved image quality using the calibration results of this work and the radar's ex-factory calibration data. The proposed novel calibration procedure improves the image quality, while considerably lowering the demands on the calibration measurements and environment.

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Section: G Problem Relaxation For Uniform Linear Arraysmentioning

confidence: 99%

“…In [6], [27]- [29], sparsity was exploited to calibrate complex gains using targets under unknown angles. Mutual coupling was considered for on-line calibration in [30] and [31]. However, these works also assumed angle measurements, thereby implying multipath free far-field conditions.…”

Section: Introductionmentioning

confidence: 99%

Antenna Array Calibration Using a Sparse Scene

Geiß

Sippel

Hehn

et al. 2021

IEEE Open J. Antennas Propag.

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“…A unique DOA estimate algorithm that integrates geometric algebra and the MUSIC algorithm was suggested for cylindrical conformal arrays with the advent of conformal antenna arrays. (Lan et al 2018) One of the paper used the joint-sparsity of the compressed sensing technique to jointly estimate the DOAs and mutual coupling coefficient with single and multiple snapshots based on the mutual coupling effect (Elbir and Tuncer 2016). Improved angle performance in bistatic MIMO radar was proposed using a multi-SVD-based subspace estimation approach.…”

Section: Introductionmentioning

confidence: 99%

Angular Resolution improvement by conformal array with the 2-D Multiple Signal Classification (MUSIC) algorithm for RADAR

Jagtap

Kunte²

2022

Preprint

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One of the most demanding requirement of RADAR system is estimation of Direction of arrival (DoA) estimation when two or more objects are very close to each other. It is quite difficult for any ranging and detection system to distinguish between them. Multiple antenna receiver technologies such as array antenna technology have advanced to the point, where they can achieve high angular resolution. Multiple antenna arrays are Planar array and Conformal array.Radiating elements are equally spread over surfaces in planar(URA) and conformal antennas apertures are of curved surface. Main problem with planar arrays is scan angles, are about +/-60 • from broadside.In conformal array, scan angle is about 360 • .This extended scan is very much useful for missiles and high speed air crafts radar, compare to planar array. So this paper checks how conformal array is better for high speed air craft’s radar system for achieving improved angular resolution. To achieve higher resolution in DoA estimation, subspace-based algorithms Multiple Signal Classification (MUSIC) is used with conformal array. This work focuses on comparing Conformal arrays and Uniform Rectangular arrays for DoA estimation. This paper examines the effect of using the MUSIC algorithm along with two different kinds of receivers to check for noise level and improved DoA resolution. Conformal array receivers shows two closely spaced objects are resolvable with 25 perecent improvement in azimuth angle and 68 perecent in elevation angle over the Uniform Rectangular Array(URA).As the number of array elements increased in conformal array,more accuracy in DOA estimation with reduced grating lobes achieved.The performance of these systems is assessed using computer simulation studies using Matlab. The findings shows conformal multi-array receiver outperforms URA receiver.

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“…Spatial spectrum estimation, also known as direction-of-arrival (DOA) estimation, is an important research content in the field of array signal processing [1][2][3][4][5][6], which has been widely applied in wireless communication, radio astronomy, sonar, speech and other fields [7][8][9][10]. Most DOA estimation algorithms are designed for uniform linear arrays (ULAs).…”

Section: Introductionmentioning

confidence: 99%

Sparse linear array with low mutual coupling ratio for DOA estimation

Cao

Feng

et al. 2021

IET Communications

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In order to reduce the mutual coupling ratio of sparse linear array, a new linear array structure with two sparse uniform linear arrays interleaved nested, is proposed in this paper. The new sparse linear array structure is consisted of two subarrays which have N and M physical sensors, respectively. By setting appropriate interelement spacing and interleaving, the degrees-of-freedom, uniform degrees-of-freedom and array aperture of the proposed sparse array can reach 2NM + 2N , 2(N + 2M) + 1 and max{(N − 1)R 1 , (M − 1)R 2 + d }, respectively. On one hand, the proposed sparse array has closed-form expressions for the sensor locations. On the other hand, through comparative analysis, although the proposed array structure has lower uniform degrees-of-freedom, it can greatly increase the degreesof-freedom, extend the array aperture, and reduce the mutual coupling ratio between physical sensors, which means better estimation performance of direction-of-arrival estimation can be achieved. Finally, the direction-of-arrival estimation performance of the proposed array structure is verified by numerical simulations. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

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2-D DOA and mutual coupling coefficient estimation for arbitrary array structures with single and multiple snapshots

Cited by 26 publications

References 38 publications

Antenna Array Calibration Using a Sparse Scene

Antenna Array Calibration Using a Sparse Scene

Angular Resolution improvement by conformal array with the 2-D Multiple Signal Classification (MUSIC) algorithm for RADAR

Sparse linear array with low mutual coupling ratio for DOA estimation

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